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Various Nanotube Scaffolds for Cell Proliferation

2009· article· en· W2128631024 on OpenAlexaff
Fumio Watari, Tsukasa Akasaka, Kosuke Ishikawa, Masaya Matsuoka, Eri Hirata, Naofumi Terada, Atsuro Yokoyama, Motohiro Uo, Sachiko Itoh, Yasutaka Yawaka, Masato Suzuki, Noriyuki Takashi, Yasunori Totsuka, Yoshimasa Kitagawa, Shigeaki Abe, I.D. Rosca, Yoshinori Kuboki, Yoshio Bando

Bibliographic record

VenueMaterials science forum · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceCarbon nanotubeNanotechnologyNanotubeAluminosilicateApatiteFilopodiaOsteoblastPorosityChemical engineeringMorphology (biology)CellComposite materialChemistry

Abstract

fetched live from OpenAlex

Carbon nanotubes (CNT) and their derivatives with different structure and compositions have unique features. In the present study, cell proliferation was performed on various nanotubes such as single walled CNTs, multiwalled CNTs and imogolite which is nanotubes of aluminosilicate. SEM observation of the growth of osteoblast-like cells cultured on CNTs showed the morphology fully developed for the whole direction, which was different from that extended to the one direction on the usual scaffold. Numerous filopodia were grown from cell edge, extended far long and combined with CNT meshwork. Apatite precipitation in simulated body fluid, affinity for proteins and saccharides, and nanosize meshwork structure with large porosity would be the properties responsible for these cell adhesion and growth. Imogolite showed the similar properties to CNTs. Nanotubes could be the favorable materials for biomedical applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.251
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2009
Admission routes1
Has abstractyes

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